Sentence Similarity
sentence-transformers
Safetensors
Azerbaijani
bert
feature-extraction
retrieval
azerbaijani
embedding
Eval Results (legacy)
text-embeddings-inference
Instructions to use LocalDoc/LocRet-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LocalDoc/LocRet-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LocalDoc/LocRet-small") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from LocalDoc/LocRet-small: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/LocalDoc/LocRet-small/resolve/main/model.safetensors
- Command line
-
hf download hf://LocalDoc/LocRet-small/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LocalDoc/LocRet-small/resolve/main/model.safetensors
471 MB
- Xet hash:
- 19985f439bc5606380097b386ab03dece069e3c1840739263ba72340e562c69b
- Size of remote file:
- 471 MB
- SHA256:
- bb0d2aa033e4b516e20a0fe1dcdf633ef57f9c5a4b69c96a19cdddacf58d45eb
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